Engineering Commons^™

Some Results Of Studying The Connection Between Geodynamic Processes And Observed Anomalous Electromagnetic Phenomena, Botir Khamidovich Khaydarov, Umar Abdullaevich Najmiddinov

Technical science and innovation

This article provides information about various cases of anomalous changes in electromagnetic fields recorded in real field conditions in seismically active areas in connection with the occurrence of earthquakes and various assessments and interpretations of the noted anomalies are carried. The main attention was focused on the consideration of the concept of changes in the conditions of waveguide propagation of atmospherics and the model of surface emitters. There is considered сevery reason to believe that both mechanisms can manifest themselves separately or together depending on the nature of the process, the rheology of the medium and other geophysical conditions, just …

Installation Of Self-Controlled Floating Bars At Water Intake Pipelines Of Pumping Stations, Oleg Yakovlevich Glovatsky, Rustam Khujakulov, Fakhriddin Jaylovovich Nasirov, Ilhom Islamov, Jorabek Abdurahman Uralov, Shakhboz Amirov

Technical science and innovation

In modern conditions, to maintain a favorable hydraulic regime on mechanical water lifting systems, it is rational to use protective structures on watercourses that use the energy of the water flow in the form of a floating tank. Based on the obtained theoretical principles, fundamentally new self-controlled floating structures were created and the hydrodynamic characteristics of the movement of an unsteady three-dimensional flow for the parameters of the wing profile were refined. The theory of unsteady three-dimensional movement of a multiphase flow with its artificial stratification and protection from selected phases in depth is used by floating guide systems at …

03.31.2025 Ored Connect, Liz Williamson

ORED Newsletter

Indirect Cost Rate Agreement

NIH Transition to Common Forms

NIH Implementation of New Initiatives and Policies

Mechanical Cleaning Of Industrial Exhaust Gases By Wet Method., A. A. Turgunov, E. A. Egamberdiev, R. F. Rashidov, A. A. Kholmurodov, D. J. Ergash

Technical science and innovation

Environmental protection is a priority area of human development. This paper presents the materials of scientific research of the creative group of the Tashkent State Technical University named after Islam Karimov, aimed at mineralization of the load on the environment, in particular on the atmospheric air of industrial enterprises. One of the more accessible solutions to this problem is the use of modern, more efficient devices for capturing and neutralizing exhaust gas emissions into the atmosphere from industry. Today, the use of mechanical methods for capturing pollutants is relevant due to the simplicity of design and operation. Wet methods for …

Adaptive Control System Of Nonlinear Dynamic Object On The Basis Of Neuro-Fuzzy Networks, Isomiddin Xakimovich Siddikov, Dilnoza Maxamadjanovna Umurzakova

Technical science and innovation

The presented paper is devoted to the development of an adaptive control system for a nonlinear dynamic object using neuro-fuzzy networks. The authors note that in real conditions dynamic objects function under conditions of uncertainty, which are characterised by complex and poorly understood relationships between technological variables, the presence of perturbing and random disturbances, as well as nonlinear elements. This makes it difficult to apply traditional linear adaptive control algorithms. The use of self-organising adaptive control is proposed, in which the mathematical model of the controlled system is formed by operational identification during system operation. It is shown that linear …

Development Of Analytical Dependencies For Determining Kinematic Parameters Of The Drive Of The Working Engine Of The Mixing Machine, N. A. Maksudova

Technical science and innovation

The requirement of any technological process of product preparation is intensive mixing. This ensures uniform distribution of components. At the initial stage of designing planetary mechanisms, special attention is paid to determining the kinematic parameters. The dimensions, weight and design of the mechanism depend on the value of these parameters. The main criterion for assessing the scheme of the planetary mechanism is the kinematic parameters of the gear wheels of the mechanism. The article presents a kinematic scheme of the planetary mechanism of the kneading machine. The principle of rotation of the gear wheels of the planetary mechanism of the …

Evaluation Of Gfap And Ptau Protein Expression In Male And Female Cci Mouse Models, Sara Wallace

Honors Program: Senior Projects (Public)

Traumatic Brain Injury (TBI) is a serious public health concern that leads to the death or disability of thousands of individuals in the US annually. Progression of TBI involves primary damage from the initial, mechanical injury and secondary damage, from nonmechanical, pathological dysfunction. The secondary damage mechanisms can be better understood, diagnosed, and treated through the quantification of TBI biomarkers. The two biomarkers of interest in this study are pTau and GFAP. The male and female mouse models showed similar significant increase in GFAP following injury, as well as a general lack of increase in pTau expression following the injury. …

Unveiling The Transformative Power Of Unsupervised Machine Learning Through Clustering, Vishnu S. Pendyala

Open Educational Resources

Clustering methods demonstrated their transformative potential across various industries through image segmentation, anomaly detection, bioinformatics, and customer segmentation. The presentation explores these techniques in unsupervised machine learning, focusing on foundational clustering algorithms such as K-means, Hierarchical Clustering, and DBSCAN. Through an in-depth analysis of their underlying principles and computational intricacies, the presentation highlights how these methods have evolved to address complex, high-dimensional data problems. The presentation provides insights into how K-means remains a versatile tool for partitioning data in linear spaces. It delves into Hierarchical Clustering's unique approach to building dendrograms and capturing multi-scale data relationships, and how DBSCAN's density-based …

Reweighting Configurations Generated By Transferable, Machine Learned Models For Protein Sidechain Backmapping, Jacob Monroe

Chemical Engineering Faculty Publications and Presentations

Multiscale modeling requires the linking of models at different levels of detail, with the goal of gaining accelerations from lower fidelity models while recovering fine details from higher resolution models. Communication across resolutions is particularly important in modeling soft matter, where tight couplings exist between molecular-level details and mesoscale structures. While multiscale modeling of biomolecules has become a critical component in exploring their structure and self-assembly, backmapping from coarse-grained to fine-grained, or atomistic, representations presents a challenge, despite recent advances through machine learning. A major hurdle, especially for strategies utilizing machine learning, is that backmappings can only approximately recover the …

Correlation Of Socioeconomic Characteristics And Maintenance Level Of Houses In Mass Housing Scheme In Ilorin, Nigeria, Oladimeji Samuel Bolaji, Abubakar-Kamar Tayo Aishat, Adeyemi Olabanji Lukman, Arosanyin Mofeoluwa Victor

Architecture and Planning Journal (APJ)

It is a common belief that certain behaviors are influenced by a person's social level. This claim is taken to apply to housing maintenance in any society, whether it is owned or rented. The aim of this study is to identify the socioeconomic indicators that are most predictive of the maintenance level of houses in mass housing schemes in the metropolis of Ilorin, Nigeria. Both primary and secondary data were used in this investigation. Qualitative and quantitative data through structured questionnaires administered on 1125 household heads constituting 27% of the sample frame were collected from sixteen (16) mass housing schemes …

Evaluating Coal-Jatropha Curcas Composite Briquettes As Sustainable Fuel Alternatives, Amad Ullah Khan, Muhammad Saleem, Muhammad Abas, Zakir Ullah, Khan Muhammad, Farida Anjum, Aamer Sharif, Melkamu Tadesse Getachew

Research outputs 2022 to 2026

Coal is a major fuel source but raises environmental concerns. This study investigated the feasibility of utilizing a composite briquette sustainable fuel produced from subbituminous coal and Jatropha curcas biomass. Briquettes were prepared with varying weight ratios of coal to J. curcas biomass (90:0–0:90) using corn starch as a binder. The influence of this ratio on the briquettes’ properties was comprehensively evaluated through proximate analysis, ultimate analysis, scanning electron microscopy (SEM), and X-ray fluorescence (XRF) analysis. The results revealed that increasing the J. curcas content in the briquettes gradually decreased the moisture content, ash content, and fixed carbon content while …

Occupational Safety Culture In Modern Aviation Maintenance, Sang-A Lee

Journal of Aviation Technology and Engineering

Aviation maintenance is paramount to the safety and efficiency of global air travel. Disturbingly, 2022 data revealed an unprecedented surge in severe injuries among aircraft maintenance technicians in the United States, prompting renewed scrutiny of the aviation maintenance occupational safety culture. In light of these developments, a systematic literature review was conducted to discern the influential factors shaping this safety culture, especially considering the industry’s rapid technological advancements. The review process involved meticulous key word searches, stringent article selection criteria, and qualitative data analysis software to interpret findings. From the synthesis of 35 peerreviewed articles, nine pivotal constructs emerged: (1) …

Exploring The Impact Of Multiwall Carbon Nanotubes On Enhancing Water-Based Mud Performance, Attia Attia, Mohamed Saad Elhossieny Dr., Hesham Abuseda Dr., Ahmed Gouish Prof., Adel Salem Prof.

Petroleum Engineering and Gas

Drilling fluids are critical components in hydrocarbon and geothermal well construction, particularly in extreme downhole environments such as deep reservoirs and high-temperature geothermal systems. Key challenges in designing water-based drilling muds (WBDM) for these applications include effective thermal management, maintenance of rheological stability, and enhancement of thermal conductivity under high-temperature, high-pressure (HTHP) conditions. Recent advances in nanotechnology suggest that nanoscale additives, such as uniformly dispersed carbon nanotubes (CNTs), can significantly improve the thermorheological performance of drilling fluids compared to conventional formulations. However, stabilizing critical fluid properties—including viscosity, filtration efficiency, mud cake integrity, and gel strength—remains a persistent challenge in WBDM …

Accurate And Scalable Control-Flow Differential Analysis On System Traces, Yuta Nakamura

College of Computing and Digital Media Dissertations

Debugging and understanding system behavior pose technical challenges, often necessitating the comparison of two audited execution traces. Although provenance systems execution traces, the audited traces at most enable causal analysis within a single known execution. As a result, utilizing provenance systems differential analysis thus for debugging and reasoning is a challenging task. This thesis addresses the challenge of using provenance in debugging by developing accurate and scalable methods for differential analysis of system provenance. Our approach emphasizes the importance of knowing the application’s provenance graph structure and embedding this graph structure information within traces to conduct a precise differential analysis …

Volatile Organic Compound (Voc) Sensing Trend Among Novel 2d/3d Materials, Mohammad Shakhawat Hossain

USF Tampa Graduate Theses and Dissertations

Volatile Organic Compounds (VOCs) present significant health risks to both humans and animals. Long term exposure to certain VOCs belonging to certain chemical classes can cause both short- and long-term effects including nausea, damage to the central nervous system, and cancer. VOCs can be found in various everyday products like varnishes, paints, cooking items, cleaning products, nail polishes etc. Because of their ubiquitous nature, health concerns and risks regarding VOC exposure have become even more pressing. In this study, the VOC sensing capabilities and trends of novel 2D, and 3D materials (perovskite, and phthalocyanines) have been explored through electrochemical and …

Automated Data Analysis For Concussion Patient Records: A Flutter-Based Desktop Application, Fhaheem Tadamarry

USF Tampa Graduate Theses and Dissertations

Concussions are a prevalent and complex medical condition requiring careful clinical assessment and data-driven insights for effective management. This thesis presents the development of an automated data analysis system for concussion patient records, integrating Flutter-based desktop application development with SQL-driven data processing. The system provides a streamlined, interactive interface for clincians and researchers to upload, visualize, and analyze patient data efficiently.

The proposed solution automates data cleaning, preprocessing, and statistical analysis, ensuring robust and reliable insights into demographic, clinical, and recovery-related factors. Key analyses include sex-based differences injury mechanisms, prior head injury impact, mood disorder correlations, and time-to-treatment variations. The …

Multimodal Ai-Driven Biomarker For Early Detection Of Cancer Cachexia, Sabeen Ahmed

USF Tampa Graduate Theses and Dissertations

Cancer cachexia is a metabolic syndrome characterized by substantial skeletal muscle loss, impacting cancer patients' survival and quality of life. Despite its clinical significance, early detection remains a challenge due to the lack of standardized diagnostic criteria and the reliance on indirect markers. This work presents an AI-driven approach to enhance cachexia detection and monitoring by integrating multiple deep learning methodologies. We explore transformer architectures for time-series analysis to model sequential medical data, enabling disease prediction and progression modeling. To ensure robust and reliable decision-making in clinical settings, we explore Bayesian deep neural networks for uncertainty estimation. Additionally, we introduce …

Enhancing Ai Reliability: Probabilistic Inference And Neural Optimization, Behnam Zeinali Rizi

USF Tampa Graduate Theses and Dissertations

Deep neural networks have recently shown better performance than traditional machine learning algorithms in various applications such as computer vision, natural language processing, indoor navigation, and biomedical signal/bio-informatics data processing tasks. However, some main challenges still exist when harnessing these models for different applications. The first challenge is the performance of these methodologies for some specific types of data, such as Biomedical images, IMU measurements, and even bioinformatics data, such as genome expression. Moreover, deploying these models on mobile and IoT devices is computationally challenging. Most devices use cloud computing, where powerful deep-learning models analyze the data on a server. …

Autonomous Underwater Vehicle Planning Using Hybrid D* Lite With Ppo And Td3: Experimental Design And Performance Analysis, Matthew J. Rice

Undergraduate Theses

Autonomous Underwater Vehicles (AUVs) face significant challenges in underwater navigation, including generating smooth paths, avoiding obstacles, and adapting to complex conditions. This paper introduces a hybrid path-planning algorithm, D-RL*, that integrates the D* Lite algorithm for efficient initial pathfinding with Deep Reinforcement Learning methods to refine paths for smoother trajectories. The proposed approach addresses D* Lite's inability to produce continuous, smooth paths and baseline Reinforcement Learnings’ failures in environments requiring significant detours. Experimental results in four progressively complex environments highlight D-RL*’s ability to plan smoother paths than D* Lite while training in a shorter amount of time and generating shorter …

Assessing Groundwater Availability And Land Subsidence Risk Associated With Anthropogenic Activities In A Complex Aquifer System, Aya Bakr Attya Mohamed

LSU Doctoral Dissertations

The Southern Hills aquifer system (SHAS) is the primary source of water in the Capital area of Louisiana. However, the overexploitation of freshwater-bearing aquifers and the presence of two active faults, the BR fault and the DSS fault, have resulted in groundwater depletion, saltwater intrusion, and increased the risk of land surface subsidence. Such critical issues pose substantial threats to groundwater availability and exert detrimental effects on the environment and urban infrastructures. This dissertation presents a comprehensive investigation of the SHAS for recognizing the consequences of groundwater depletion and its potential long-term impacts on groundwater availability and land stability. A …

Quantitative Risk Analysis For Elections, George A. Buras

LSU Master's Theses

This paper examines risk analysis and risk management in the field of election security. The purpose of this paper is not to enumerate risks to election security or explain how they might be mitigated, but rather to understand and improve how we measure and communicate those risks.

First, I contextualize election security risks by establishing what it means for an election to be secure and I give an overview of the types of events that might threaten election security. Then, I explore different methods that we can use to model electoral risks. Existing resources for managing electoral risks use qualitative …

Stable Heteroclinic Channels As A Decision-Making Model: Overcoming Low Signal-To-Noise Ratio With Mutual Inhibition, Natasha A. Rouse

Faculty Scholarship

Bio-inspired robot controllers are becoming more complex as we strive to make them more robust to, and flexible in, noisy, real-world environments. A stable heteroclinic network (SHN) is a dynamical system that produces cyclical state transitions using noisy input. SHN-based robot controllers enable sensory input to be integrated at the phase-space level of the controller, thus simplifying sensor-integrated, robot control methods. In this work, we investigate the mechanism that drives branching state trajectories in SHNs. We liken the branching state trajectories to decision-splits imposed into the system, which opens the door for more sophisticated controls-all driven by sensory input. This …

Study On Dopamine Electrochemical Sensing Based On Au@Mos2, Ning An, Ni Su, Xin-Ran Li, Jian-Yu Liu, Qi-Yan Wang

Journal of Electrochemistry

Dopamine (DA) is a vital neurotransmitter, and accurate detection of its concentration is critical for both clinical diagnostics and neuroscience research. Due to its electrochemical activity, DA is commonly detected using electrochemical methods, which are favored for their simplicity, fast response time, and suitability for in vivo analysis. In this work, a highly sensitive DA electrochemical sensor was developed using an Au@MoS₂ composite, created by modifying molybdenum disulfide (MoS₂) nanosheets with gold nanoparticles through HAuCl₄ reduction, and it was aimed at enhancing DA adsorption and improving detection performance. Scanning Electron Microscopy (SEM), transmission electron microscopy (TEM), …

Recent Advances In Non-Enzymatic Electrochemical Sensors For Theophylline Detection, Gustria Ernis, Yulia M T A Putri, Muhammad Iqbal Syauqi, Prastika Krisma Jiwanti, Yeni Wahyuni Hartati, Takeshi Kondo, Qonita Kurnia Anjani, Jarnuzi Gunlazuardi

Journal of Electrochemistry

Detection of target analytes at low concentrations is significant in various fields, including pharmaceuticals, healthcare, and environmental protection. Theophylline (TP), a natural alkaloid used as a bronchodilator to treat respiratory disorders such as asthma, bronchitis, and emphysema, has a narrow therapeutic window with a safe plasma concentration ranging from 55.5–111.0 μmol·L^–1 in adults. Accurate monitoring of TP levels is essential because too low or too high can cause serious side effects. In this regard, non-enzymatic electrochemical sensors offer a practical solution with rapidity, portability, and high sensitivity. This article aims to provide a comprehensive review of the recent developments …

In-Situ Electrodeposition Of Feco-Mof On Au Ultramicroelectrode For Highly Sensitive Detection Of Epinephrine, Yan Chen, Shang Jian, Si-Yu Wan, Xiao-Tong Cui, Zhong-Gang Liu, Zheng Guo

Journal of Electrochemistry

Metal-organic framework (MOF) nanostructures have emerged as a prominent class of materials in the advancement of electrochemical sensors. The rational design of bimetallic MOF-functionalized microelectrode is of importance for improving the electrochemical performance but still in great challenge. In this work, the bimetallic FeCo-MOF nanostructures were assembled onto a gold disk ultramicroelectrode (Au UME, 5.2 μm in diameter) via an in-situ electrodeposition method, which enhanced the sensitive detection of epinephrine (EP). The in-situ electrodeposited FeCo-MOF exhibited a characteristic nanoflower-like morphology and was uniformly dispersed on the Au UME. The FeCo-MOF/Au UME demonstrated excellent electrochemical performance on the detection of EP …

Scalable Mxene-Based Textile Supercapacitors, Abaigeal Aydt

Honors Program: Senior Projects (Public)

The demand for flexible and wearable energy storage devices for portable applications has led to the exploration of textile-based supercapacitors (TSCs). TSCs will allow for the creation of a new class of energy harvesting and storing technology directly into our clothing and will require using non-toxic and/or biocompatible materials. This will result in a greener and more sustainable path to address the challenges at the nexus of energy, mobility, and sustainability. To fabricate a TSC, a yarn made of fibers, such as wool or cotton, is coated with MXene flakes; MXenes are composed of transition metal carbides, nitrides, or carbonitrides …

Exploring Corona Discharge In Electrostatic Printing For Electronics And In Other Application, Zijian Weng

USF Tampa Graduate Theses and Dissertations

The field of printed electronics (PEs) is expanding rapidly, driven by increasing market demand. According to reports, the global market for PEs is expected to reach $23 billion by 2026, with a compound annual growth rate of 18.3% from 2023 to 2028. This growth necessitates the development of innovative printing technologies that can meet these demands efficiently, delivering high-quality, high-resolution PEs suitable for applications in health, environmental monitoring, sports, aerospace, and more.

Currently, PEs manufacturing relies on two main groups of printing technologies. Contact printing methods offer high-speed production but struggle with precision, while non-contact methods provide high resolution but …

Robust Spacecraft Autonomy For Deep Space Exploration In Special Euclidean Group Se(3), Matthew Wittal

Doctoral Dissertations and Master's Theses

Over the past half-century, humanity has gained extensive experience conducting manned spaceflight near Earth. Arguably, "near Earth" could even include the Moon — the most distant destination humans have reached. However, "near" in this work primarily refers low Earth orbit (LEO). One could argue that we have not truly left Earth since the Apollo, as spacecraft in some LEOs remain subject to atmospheric drag thus emphasizing their continued connection to Earth's immediate environment. Reflecting on this, it becomes clear that humanity has largely remained bound to Earth’s immediate vicinity since the Apollo missions reached the Moon. However, that is set …

Web Application For Simulation Of An Agent-Based Model In Netlogo3d, Chris Davis Perumal, Abraham Nofal, Benedict J. Kolber, Rachael Miller Neilan

Spora: A Journal of Biomathematics

Agent-based models (ABMs) are computer simulation models for studying systems of autonomous agents. Modelers often use specialized software like NetLogo to develop ABMs, but this software poses barriers to researchers in other disciplines with no prior programming experience. To address this issue, we developed a web application that allows users to simulate our ABM via a web browser, eliminating the need for the user to download and use specialized software. While presented in the context of a specific ABM, our approach can be applied to other ABMs to enhance accessibility. The ABM presented here was developed in NetLogo3D. The model …

Retracted: Image Denoising: Smooth Total Variation Minimization For 5g Enhanced Mobile Broadband Transmission System, Shehab Ahmed Ibrahem, Walled Khalid Khalid Abdulwahab, Moceheb Lazam Lazam Shuwandy

Iraqi Journal for Computer Science and Mathematics

Image denoising is an important area of computer vision. Rudin-Osher-Fatemi model based on a gradient is one of the simplest models used in image denoising to solve the problem of restoring the clear image. The challenge in solving this model is the non-differentiability of Total Variation function (TV-function) minimization. Image transmission is widespread over wireless systems, including the fifth generation (5G) cellular network. Transmission impairment can affect transmitted images, including noise, attenuation, and distortion. This study proposed a new smoothing technique to make the TV-function differentiable and smooth. The new smoothed function was used for de-noising images with the help …